This doctoral thesis analyses whether electric vehicle is technical, economic and environmental sustainable. We have studied a company fleet of electric vehicles which has a carsharing service for the retail department to know if the EV could replace an internal combustion engine vehicle.
We have examined the journeys of 8 EV located on six of the main cities of Spain through data collected from the CAN bus UCV (on-board diagnostics). We have measured the battery's charging, because we are interested on its behaviour (autonomy, auto-discharging and aging) and the energy required to charge the EV. Also, we have studied the well to wheels analysis, assessing their efficiency and environmental effects (CO2 emissions and noise), quantifying the economic impact (fuel and Total Cost of Ownership) and other potential benefits associated with EV (Corporate Social Responsibility, tax free, etc).

The module CDMtek-PM has been developed with the needs of the electrical engineering students in mind. It is intended to serve as a platform to begin to consolidate the theoretical knowledge learned during the classes by providing a practical tool where they can program the software, for example with the CDMtek-DS module, and then observe, analyse and make real-time measures of the electrical and mechanical part of an electrical drive.

The incorporation of high levels of small-scale non-dispatchable distributed generation is leading to the transition from the traditional 'vertical' power system structure to a 'horizontally-operated' power system, where the distribution networks contain both stochastic generation and load (such as electric vehicles recharging). This fact increases the number of stochastic inputs and dependence structures between them need to be considered. The deterministic analysis is not enough to cope with these issues and a new approach is needed. Probabilistic analysis provides a better approach.
This PhD thesis describes the grid impact analysis of charging electric vehicles (EV) using charging curves with detailed battery modelling. A probabilistic method using Monte Carlo was applied to a typical Spanish distribution grid, also using mobility patterns of Barcelona. To carry out this analysis, firstly, an IEEE test system was adapted to a typical distribution grid configuration; secondly, the EV and its battery types were modeled taking into account the current vehicle market and the battery characteristics; and, finally, the recharge control strategies were taken in account.
Once these main features were established, a statistical probabilistic model for the household electrical demand and for the EV charging parameters was determined. With these probabilistic models, the Monte Carlo analysis was performed within the established scenario in order to study the lines' and the transformers' loading levels. The results show that an accurate model for the battery gives a more precise estimation about the impact on the grid. Additionally, mobility patterns have been proved to be some of the most important key aspects for these type of studies.

For the last years, PV (photovoltaic) generation has been having an important impact on LV (low voltage) and MV (medium voltage) grids in Spain, due to the increasing number of installations. As power monitoring of the generation is in most cases not required, utilities are forced to make assumptions on PV power generation in order to perform network planning studies for both peak demand and contingency analysis. These assumptions increase errors committed during the analysis, as the number of PV installations increases. This paper presents a methodology for estimating PV active power generation values for planning purposes in MV and LV power systems, from historic generation data, based on the development of correlation models. This methodology is applied to three different examples, using predictors based on real registered data. The methodology was also applied in a typical grid study and it's error was determined. (C) 2013 Elsevier Ltd. All rights reserved.

The reconfiguration of a power distribution system, by exchanging the functional links between its elements, represents one of the most important procedures to improve the performance in the operation of a distribution system. The optimization through reconfiguration (or optimal reconfiguration) of a power distribution system is not a new problem but still represents a difficult one and is specified in some strategies for smart grids. The paper addresses this problem as a single objective one, where, as main criterion, active power losses have been chosen. There is no unique acceptance regarding which approach (based on heuristics, meta-heuristics, genetic algorithms, etc.) is the most proper to use in order to solve this problem. The most important thing is how the specific knowledge of the problem domain is used and modeled in the implementation. Moreover, the indices which can quantify the quality of a reconfiguration method consist in runtime and the obtained solution and these indices can be confirmed only by experimental results. In order to solve the problem (to search and find the optimal solution) an original genetic algorithm based on connected graphs is proposed. Comparative tests performed on some test systems demonstrated the accuracy and the promptness of the proposed algorithm. AbbreviationsPactive power lossesVinodes voltagesI ijelectric current through a branch ijijbinary variable representing the status of a tie line (0 - open, 1 - closed)nthe number of electric system nodespthe number of connected componentsXthe set of power system nodesEthe set of power system lines (branches).

The NGO Misión y Desarrollo para Goundi, with the collaboration of the technology transfer centre CITCEA-UPC and the support of the CCD-UPC, is carrying out since 2011 the project Pôle Goundi aiming to electrify Goundi, a village located in the South of Chad.
In this sense, the construction of a small-scale power plant which will use local resources to generate electricity is planned. Although the plant is expected to use photovoltaic and thermal solar energies also, biomass gasification has also
been prioritized due to the social and economical advantages of spurring agricultural activity in Goundi.
Since the installation of the power plant will be done by stages, the first stage of the project has to demonstrate its viability by installing and operating the first 20kW of electrical power. For this, a complete commercial solution which is
able to gasify woody biomass has been selected. Currently, the system is being tested before its shipment to Chad and a model which simulates its behaviour has been developed.

This paper presents the use of emulator devices to represent different elements of a microgrid system. In this sense, the emulation concept and its advantages are explained. Each emulator is implemented by means of power converters which receive a determined power reference according to the energy resource that it means. Therefore, connecting a determined number of these emulators into the same system it is possible to create several microgrid configurations, which will be capable of performing different test and obtaining the same result that in a real system. In the end, as an example of the advantages that the emulators are able to offer, an experimental platform is presented.

This work deals with the modeling, control and experimental validation of a flywheel-based energy storage device. The system is based on a low-speed rotating disk mechanically coupled to a Permanent Magnet Synchronous Machine (PMSM). The electrical power is exchanged with the external grid by means of a set of back-to-back power converters. These power electronics control the speed of the machine, and thus the active power absorbed or injected by the device, and also regulate the reactive power at the point of common coupling with the external grid. Vector control techniques are used for designing the converter controllers: a field oriented vector control algorithm is implemented for governing the servomotor while an instantaneous power theory-based algorithm is used to manage the active and reactive currents flowing from the grid side converter. The control implementation in the experimental setup has been carried out by means of programming Digital Signal Processors (DSP's). The modeling and control system design has been validated after executing several experiments. Other characteristics such as the torque losses of the system as well as the system performance concerning energy rating, power rating and energy efficiency characteristics are determined experimentally.

Reconfiguration, by exchanging the functional links between the elements of the system, represents one of the most important measures which can improve the operational performance of a distribution system. The authors propose an original method, aiming at achieving such optimization through the reconfiguration of distribution systems taking into account various criteria in a flexible and robust approach. The novelty of the method consists in: the criteria for optimization are evaluated on active power distribution systems (containing distributed generators connected directly to the main distribution system and microgrids operated in grid-connected mode); the original formulation (Pareto optimality) of the optimization problem and an original genetic algorithm (based on NSGA-II) to solve the problem in a non-prohibitive execution time. The comparative tests performed on test systems have demonstrated the accuracy and promptness of the proposed algorithm.

In this thesis it have been explained the problems that the electric distribution companies in Spain have to plan and operate
their power networks, having no detailed measurements of instant active power of a large number of non-programmable
generators connected to them. The main objective is to reduce errors and difficulties that this lack of information generates.
It has been analyzed the specific case of photovoltaic generators (PV), representing at the end of 2011, a 94.6 % of the
special regime generators connected to the power networks in Spain, and have an average power of 72 kW per plant at the
end of 2011. This means that are mainly connected to the distribution network, so we study the specific issues regarding the
planning of the distribution network.
It is defined that prediction models of solar irradiance are divided into parametric and decomposition. The ASHRAE
parametric model prediction of solar irradiance is described, checking that its instant error levels are not negligible when
compared with real data, since it does not include components that provide greater instant solar irradiance variability, such
as atmospheric phenomena.
It has been described a model based on the usability for the prediction of instantaneous power of PV generation, which is
based on an hourly rate of sunlight (Kt) to transfer the extraterrestrial solar irradiation to a horizontal surface on Earth ¿s
surface. It has been seen that the definition of the statistical function that defines Kt, makes the difference between the
different models based on usability.
It has been developed a proposed solution, which allows the development of models using predictors measured at the
Earth¿s s urface, which incorporate the variability of atmos pheric phenomena. It has been evaluated the available data for the
distribution companies, as well as specified the conditions necessary to develop specific models to be applied in distribution
network planning.
The proposed solution consists in a systematic methodology for developing models, based on historical data, which
provides a response to a wide range of applications for distribution network analysis. It has been shown that the geographic
scope of validity of the developed models exceeds the average needs for distribution network planning. It have been
developed three case studies, where application of the methodology has been developed, based on real data of a
distribution network in the province of Lleida, Spain.
Also, it has been found that the models needed for photovoltaic plants with solar follower are different from those needed for
photovoltaic plants without follower, because they need to be developed from different predictors.
Contributions have been developed based on examples of application of the developed models to network analysis, based
on another set of real data from the distribution network in Lleida, corresponding to a medium voltage line (25 kV). Based on
this example it have been described the possible options when applying the methodology, as well as several different
situations, drawing conclusions.
Furthermore, it have been evaluated the possible seasonality of the models, and therefore, the contribution that would get
from the development of specific models for each quarter, against the development of a single model for the prediction of the
whole year.
Barcelon

This paper describes a grid impact analysis of charging electric vehicles (EV) using charging curves with detailed battery modelling. A probabilistic method using Monte
Carlo was applied to a typical Spanish distribution grid, also using mobility patterns of Barcelona. To carry out this analysis, firstly, an IEEE test system was adapted to a typical distribution grid configuration; secondly, the EV and its battery types were modeled taking into account the current vehicle market and the battery characteristics; and, finally,
the recharge control strategies were taken into account. Once these main features were
established, a statistical probabilistic model for the household electrical demand and for the EV charging parameters was determined. Finally, with these probabilistic models, the Monte Carlo analysis was performed within the established scenario in order to study the lines’ and the transformers’ loading levels. The results show that an accurate model for the battery gives a more precise estimation about the impact on the grid. Additionally, mobility patterns have been proved to be some of the most important key aspects for these type of studies.

This work deals with the modeling, control and experimental validation of a flywheel test bench which is part of IREC's lab-scale microgrid. The storage device has been designed as a proof of concept. It is based on a low-speed rotating disk mechanically coupled to a Permanent Magnet Synchronous Machine. The electrical power is exchanged with the external grid by means of a set of back-to-back power converters. These power electronics control the speed of the machine, and thus the active power absorbed or injected by the device, and also regulate the reactive power at the point of common coupling with the external grid. Vector control techniques are used for designing the converter controllers: a field oriented vector control algorithm is implemented for governing the servomotor while the instantaneous power theory-based algorithm is used to manage the active and reactive currents flowing from the grid side converter. The control implementation in the experimental setup has been carried out by means of programming Digital Signal Processors (DSP's). The modeling and control system design has been validated after executing several experiments.

This work deals with the modeling, control and experimental validation of a flywheel test bench which is part of IREC’s lab-scale microgrid. The storage device has been
designed as a proof of concept. It is based on a low-speed rotating disk mechanically coupled to a Permanent Magnet Synchronous
Machine. The electrical power is exchanged with the external grid by means of a set of back-to-back power converters. These
power electronics control the speed of the machine, and thus the active power absorbed or injected by the device, and also
regulate the reactive power at the point of common coupling with the external grid. Vector control techniques are used for
designing the converter controllers: a field oriented vector control algorithm is implemented for governing the servomotor while the instantaneous power theory-based algorithm is used to manage the active and reactive currents flowing from the grid side
converter. The control implementation in the experimental setup has been carried out by means of programming Digital Signal
Processors (DSP’s). The modeling and control system design has been validated after executing several experiments.

This paper describes the modelling and control of a micro-wind generation system, based on an axial flux permanent magnet synchronous generator (PMSG), for isolated low power DC micro grids. The system consists of a micro-wind turbine including a furling tail, a PMSG, a three phase diode rectifier and a buck converter connected to a battery bank and a load. Furthermore, it incorporates a control system to extract the maximum power output from the wind turbine using the minimum possible number of sensors. The system is simulated in Matlab/Simulink to analyze the dynamical response and it is compared with the current IT-PE-100.